Jurnal Ilmiah Komputer dan Informatika KOMPUTA
Edisi...Volume..., Bulan 20..ISSN :2089-9033
Table 9 Probability Density Value Data Testing
Then calculate the value of evidence and posterior Evidence =
0.25 x 0 x 0 x 0.0001 x 0 x 0 + 0.25 x 0 x 0 x 0 x 0 x 25.2196
+ 0.25 x 0 x 0.0001 x 0 x 0 x 0.0361 + 0.25 x 21.2009 x 0.0138 x 0 x 0 x 0.1358
= 0.0000001 Posterior ALL = PALL . PSRE | ALL . PLRE
| ALL. PGLU | ALL. PRLU | ALL. PRPC | ALL Evidence
Posterior ALL =0.25 x 0 x 0 x 0.0001 x 0 x 0 0.0000001 = 1
Posterior AML = PAML . PSRE | AML . PLRE | AML. PGLU | AML. PRLU | AML.
PRPC | AML Evidence Posterior AML = 0.25 x 0 x 0 x 0 x 0 x 25.2196
0.0000001 = 0 PosteriorCLL = PCLL . PSRE | CLL . PLRE |
CLL. PGLU | CLL. PRLU | CLL. PRPC | CLL Evidence
PosteriorCLL = 0.25 x 0 x 0.0001 x 0 x 0 x 0.0361 0.0000001 = 0
PosteriorCML = PCML . PSRE | CML . PLRE | CML. PGLU | CML. PRLU | CML.
PRPC | CML Evidence PosteriorCML = 0.25 x 21.2009 x 0.0138 x 0 x 0
x 0.1358 0.0000001 = 0.000001
2.5 Implementation Interface Implementation Interface explain and describe the
implementation of each of the existing processes in this system:
Picture 10 Display Main Menu
Picture 11 Menu Display Processing
Picture 12 Training Menu Display
Picture 13 Display Menu Tests
3. CONCLUSION Based on the results of the testing that has been
done, it was concluded that the naïve Bayes method can classify the input image by statistical data
directly comparing the closest distance to the training. Testing image classification based on the
texture using image data that has been trained to have an average accuracy rate of 100 and for the
Jurnal Ilmiah Komputer dan Informatika KOMPUTA
Edisi...Volume..., Bulan 20..ISSN :2089-9033
image that has not been trained in the average accuracy rate of 90 and the level of accuracy using
three training data is 85 and the use of four training
data is
90 .
From the results of the entire test, naïve Bayes algorithm produces 91.25 accuracy rate with a
total of 20 training data and 20 test data. 4. BIBLIOGRAPHY
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